Identifying Relations for Open Information Extraction

@inproceedings{Fader2011IdentifyingRF,
  title={Identifying Relations for Open Information Extraction},
  author={Anthony Fader and Stephen Soderland and Oren Etzioni},
  booktitle={EMNLP},
  year={2011}
}
Open Information Extraction (IE) is the task of extracting assertions from massive corpora without requiring a pre-specified vocabulary. This paper shows that the output of state-ofthe-art Open IE systems is rife with uninformative and incoherent extractions. To overcome these problems, we introduce two simple syntactic and lexical constraints on binary relations expressed by verbs. We implemented the constraints in the REVERB Open IE system, which more than doubles the area under the precision… CONTINUE READING
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  • More than 30% of REVERB’s extractions are at precision 0.8 or higher— compared to virtually none for earlier systems.
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